Triple
T15701503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xueshan Range |
E380603
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Taoshan
Taoshan is a prominent mountain peak in Taiwan known for its scenic alpine landscapes and popular hiking trails.
|
E1182780
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Taoshan | Statement: [Xueshan Range, contains, Taoshan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taoshan Context triple: [Xueshan Range, contains, Taoshan]
-
A.
Jiaoshan
Jiaoshan is a scenic island and historic site in the Yangtze River near Zhenjiang, known for its ancient temples, stone inscriptions, and natural beauty.
-
B.
Songshan
Songshan is one of China's Five Great Mountains, renowned as a sacred Taoist and Buddhist site and home to the historic Shaolin Monastery.
-
C.
Tianshou Mountain
Tianshou Mountain is a notable mountain in China, recognized for its scenic landscapes and cultural significance.
-
D.
Tiantai Mountains
The Tiantai Mountains are a mountain range in eastern China renowned as the birthplace and spiritual center of the Tiantai school of Mahayana Buddhism.
-
E.
Liushi Shan
Liushi Shan is a prominent high-altitude peak in western China, recognized as the highest summit in the Kunlun Mountains range.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Taoshan Triple: [Xueshan Range, contains, Taoshan]
Generated description
Taoshan is a prominent mountain peak in Taiwan known for its scenic alpine landscapes and popular hiking trails.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Taoshan Target entity description: Taoshan is a prominent mountain peak in Taiwan known for its scenic alpine landscapes and popular hiking trails.
-
A.
Jiaoshan
Jiaoshan is a scenic island and historic site in the Yangtze River near Zhenjiang, known for its ancient temples, stone inscriptions, and natural beauty.
-
B.
Songshan
Songshan is one of China's Five Great Mountains, renowned as a sacred Taoist and Buddhist site and home to the historic Shaolin Monastery.
-
C.
Tianshou Mountain
Tianshou Mountain is a notable mountain in China, recognized for its scenic landscapes and cultural significance.
-
D.
Tiantai Mountains
The Tiantai Mountains are a mountain range in eastern China renowned as the birthplace and spiritual center of the Tiantai school of Mahayana Buddhism.
-
E.
Liushi Shan
Liushi Shan is a prominent high-altitude peak in western China, recognized as the highest summit in the Kunlun Mountains range.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f6e965881909319f85c51c6fb74 |
completed | April 16, 2026, 2:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb03539c081908b5df46bb810b949 |
completed | May 9, 2026, 10:07 p.m. |
| NEDg | Description generation | batch_69ffb13fdb6c819091c3ee5c1f199031 |
completed | May 9, 2026, 10:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb208aef881909b3a00e0015c27df |
completed | May 9, 2026, 10:15 p.m. |
Created at: April 10, 2026, 4:45 a.m.